Generation and visualization of multiple stats on TCGA expression data via TCGAbiolinks package
Access the TCGA dataset through TCGAbiolinks package.
- Get mRNA query
- Get miRNA query
- Run queries
- Parse data in more friendly dataframes:
TCGA_curated_dataset.RData(Samples with matched Clinical data, mRNA and miRNA expression)TCGA_curated_dataset.mRNAonly.RData(Samples with matched Clinical data and mRNA expression)
Functions for data extraction from the curated dataset TCGA_curated_dataset.RData.
extract_curated(project, genes, mirnas, clinical_data)
Extract data from specific project for genes, miRNA and clinical data.
extract_all_curated(genes, mirnas, clinical_data)
Extract arbitrary data from all the projects available in a single dataframe.
plotExprCancer(gene, max_y_value=NULL)
Plot gene expression profile across all tumor projects.
plotExprCancerVsNormal(gene, max_y_value=NULL)
Plot gene expression profile across all projects for paired tumor vs normal samples, when available.
plotExprCancerVsMetastasis(gene, max_y_value=NULL)
Plot gene expression profile across all projects for paired primary tumor vs metastasis samples, when available.
doKaplanMeier(cfu, label, stoptime_analysis=NULL, stoptime_plot=NULL)
Parse survival data cfu generated by geneSurvival(), fit Cox Proportional hazards model and plot results as Kaplan-Meier plot.
geneSurvival(project, gene, percentile, stoptime_analysis=NULL, stoptime_plot=NULL)
Wrapper function for doKaplanMeier() to extract percentiles of gene expression and plotting survival resuls.
microSurvival(project, mirna, percentile, stoptime_analysis=NULL, stoptime_plot=NULL)
Wrapper function for doKaplanMeier() to extract percentiles of miRNA expression and plotting survival resuls.
plotPairedBiKM(project, gene, mirna, percentile, stoptime_analysis=NULL, stoptime_plot=NULL)
Plot survival analysis for a matched gene-miRNA pair in a specific project.
generateAllPairedKMs<-function(gene, micro, percentile, stoptime_analysis=NULL, stoptime_plot=NULL)
Plot survival analysis for a matched gene-miRNA pair in all the projects available.
Functions for gene expression data extraction from the curated dataset TCGA_curated_dataset.mRNAonly.RData
The plotting and statistics of many of these functions are improved from their homologues in TCGAcurated.R.
extract_curated(project, genes, clinical_data)
Extract data from specific project for genes and clinical data
extract_all_curated(genes, clinical_data)
Extract arbitrary data from all the projects available in a single dataframe.
plotExprCancer(gene, max_y_value=NULL)
Plot gene expression profile across all tumor projects.
plotExprCancerVsNormal(gene, max_y_value=NULL)
Plot gene expression profile across all projects for paired tumor vs normal samples, when available.
plotExprCancerVsMetastasis(gene, max_y_value=NULL)
Plot gene expression profile across all projects for paired primary tumor vs metastasis samples, when available.
plotAllExpr<-function(gene,max_y_value=NULL)
Wrapper function to run plotExprCancer(), plotExprCancerVsNormal() and plotExprCancerVsMetastasis() in a single shot.
p2sym(pvalue)
Transforms numeric value into 0-to-3 asterisks notation.
doKaplanMeier(cfu, label, stoptime_analysis=NULL, stoptime_plot=NULL, make_plot=TRUE)
Parse survival data cfu generated by geneSurvival(), fit Cox Proportional hazards model and plot results as Kaplan-Meier plot.
geneSurvival(project, gene, percentile, stoptime_analysis=NULL, stoptime_plot=NULL, make_plot=TRUE)
Wrapper function for doKaplanMeier() to extract percentiles of gene expression and plotting survival resuls.
generateAllKMs(gene, percentile, stoptime_analysis=NULL, stoptime_plot=NULL, make_plot=TRUE, show_messages=T)
Plot survival analysis for a gene in all the projects available.
plotExprCancer_surv(gene, percentile, title="")
Variant of plotExprCancer() function. It plots gene expression boxplots across all projects showing the prognostic value of the gene as a color of the label axis (better (green) or worse (red) outcome). It also returns stats about expression values and prognostic value across all the projects.
plotExprCancerVsNormal_stats(gene, title="")
Variant of plotExprCancerVsNormal() function that returns statistics about the pairwise comparisons between tumor vs normal samples.
plotExprCancerVsMetastasis_stats(gene, title="")
Variant of plotExprCancerVsMetastasis() function that returns statistics about the pairwise comparisons between primary tumor vs metastasis samples.
Script employing rmarkdown to generate all the .html pages through rendering of geneTab.Rmd. The parallel implementation of this scripts is still buggy (resolve sporadic pandoc error due to concurrent instances of pandoc) but saves a lot of time (~30' vs ~5h whith 14 threads on 300 genes).
Rmarkdown file for rendering a single html page containing all the informations regarding the genes in enzymes.txt.
Generates a searchable index files with all the rendered entries in enzymes.txt.
Tab-delimited file containing a brief explanation of all the acronyms used for describing table values. It is used as an input by geneTab.Rmd.
Tab-delimited file containing all the cancer types corresponding to TCGA project codes. It is used as an input by geneTab.Rmd.
Tab-delimited file containing a list of all the genes of interest, their ENSEMBL_ID and a brief description. It is used as an input by geneTab.Rmd and index.Rmd.
Example of a page generated as an output by geneTab.Rmd.
| File | Size | md5sum |
|---|---|---|
| TCGA_curated_dataset.RData | 2.7GB | d647a96306d6c7ba505b612cc64a41e4 |
| TCGA_curated_dataset.mRNAonly.RData | 2.8GB | fd874ed9e5ee959262f595d31bbd62a3 |